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Artificial Neural Networks in Pattern Recognition

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Cover of 'Artificial Neural Networks in Pattern Recognition'

Table of Contents

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    Book Overview
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    Chapter 1 Graph Augmentation for Neural Networks Using Matching-Graphs
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    Chapter 2 A Novel Representation of Graphical Patterns for Graph Convolution Networks
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    Chapter 3 Minimizing Cross Intersections in Graph Drawing via Linear Splines
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    Chapter 4 Multi-stage Bias Mitigation for Individual Fairness in Algorithmic Decisions
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    Chapter 5 Do Minimal Complexity Least Squares Support Vector Machines Work?
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    Chapter 6 A Review of Capsule Networks in Medical Image Analysis
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    Chapter 7 Introducing an Atypical Loss: A Perceptual Metric Learning for Image Pairing
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    Chapter 8 Wavelet Scattering Transform Depth Benefit, An Application for Speaker Identification
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    Chapter 9 Sequence-to-Sequence CNN-BiLSTM Based Glottal Closure Instant Detection from Raw Speech
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    Chapter 10 Mono vs Multilingual BERT for Hate Speech Detection and Text Classification: A Case Study in Marathi
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    Chapter 11 Transformer-Encoder Generated Context-Aware Embeddings for Spell Correction
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    Chapter 12 Assessment of Pharmaceutical Patent Novelty with Siamese Neural Networks
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    Chapter 13 White Blood Cell Classification of Porcine Blood Smear Images
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    Chapter 14 Medical Deepfake Detection using 3-Dimensional Neural Learning
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    Chapter 15 A Study on the Autonomous Detection of Impact Craters
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    Chapter 16 Utilization of Vision Transformer for Classification and Ranking of Video Distortions
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Title
Artificial Neural Networks in Pattern Recognition
Published by
Springer International Publishing, November 2022
DOI 10.1007/978-3-031-20650-4
ISBNs
978-3-03-120649-8, 978-3-03-120650-4
Editors

El Gayar, Neamat, Trentin, Edmondo, Ravanelli, Mirco, Abbas, Hazem

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